| Autor: |
Maioli, Federico, Weigel, Benjamin, Lindmark, Max, Manfredi, Chiara, Zupa, Walter, Bitetto, Isabella, Russo, Tommaso, Casini, Michele |
| Předmět: |
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| Zdroj: |
Ecosphere; Nov2024, Vol. 15 Issue 11, p1-21, 21p |
| Abstrakt: |
Chondrichthyans (sharks, rays, skates, and chimaeras) make up one of the oldest and most ecologically diverse vertebrate groups, yet they face severe threats from fishing, necessitating improved management strategies. To effectively manage these species, we need to understand their spatial interactions with fisheries. However, this understanding is often challenged by limited data on chondrichthyan catches and species identification. In such cases, assessing potential risks from fishing activities can provide valuable insights into these spatial interactions. Here, we propose a method combining geostatistical models fitted to a fishery‐independent dataset with vessel monitoring system (VMS) data to estimate the spatial overlap between chondrichthyans and fishing. Our case study focuses on the western Adriatic Sea in the Mediterranean, examining the overlap between bottom trawling (including otter bottom trawling and beam trawling) and demersal chondrichthyans. We find that the northwestern part of the basin is a hotspot where threatened chondrichthyans (classified as Vulnerable, Endangered, or Critically Endangered by the International Union for Conservation of Nature Red List) greatly overlap with bottom trawling activities. Moreover, some areas, such as the northernmost part of the Adriatic and the "area dei fondi sporchi" in the north‐central offshore part, exhibit minimal overlap between threatened chondrichthyans and bottom trawling, potentially serving as refuges. We recommend prioritizing the management of otter bottom trawling in the northwestern basin to protect these threatened species, while also paying attention to the possible impacts of beam trawling on skates and chondrichthyan habitats. Despite certain limitations, our findings demonstrate that combining geostatistical models of species distributions with VMS data is a promising method for identifying areas of concern for species vulnerable to fishing. This approach can inform targeted management measures and cost‐effective onboard monitoring programs. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
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